scholarly journals ANALISIS PERILAKU PENGENDARA DAN JARAK PANDANG HENTI SEPEDA MOTOR MATIC

2018 ◽  
Vol 1 (2) ◽  
pp. 55
Author(s):  
Erika Buchari ◽  
Ahmad Gilang Dwi Junanta
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Sight Distance ◽  
Moving Vehicles ◽  
Braking Distance ◽  
Motorcycle Industry ◽  
Multi Linear Regression ◽  
Stopping Sight Distance ◽  
The Relationship ◽  
The Ideal

The growth of Matic-Motorcycle in Indonesia is increased steeply lately. According to Assosiasion of Indonesian Motorcycle Industry, AISI the sales of matic motorcycle have achieved 75,49% (3,639,000) of the wholesaler 4,821,000. In fact, motorcycle users do not realize that automatic motorcycle’s characteristics especially braking distance are different with those of non-automatic motorcycles. The different way of riding can cause uncontrolled vehicles during braking, when promptly change speed either faster or slower. Stopping sight distance is the distance needed by riders in order to stop their moving vehicles after seeing the obstacles in the front. This research is seeking to know the behavior of motorcycle users and stopping sight distance that is ideal for the users of automatic motorcycles. Multi linear Regression model is made to find out the relationship between stopping sight distance and other variables such as speed, machine capacity, type of brakes etc. From this model, it can be derived the ideal stopping sight distance which is affected by speed, machine capacity, type of front brakes. Perkembangan sepeda motor matic di Indonesia mengalami pertumbuhan yang sangat pesat beberapa tahun belakangan ini. Menurut data dari asosiasi industri sepeda motor Indonesia( AISI,2015) penjualan sepeda motor matic mengalami pertumbuhan yang sangat pesat dibandingkan dan motor bebek dan sport, yaitu 75,49% (3,639 juta matic dari penjualan 4,821 juta motor keseluruhan). Fakta di lapangan, pengguna tidak menyadari beda karakteristik kendaraan motor matic dengan non matic. Perbedaan ini mengakibatkan tidak terkontrolnya kecepatan kendaraan dimana seringnya terjadi perubahan percepatan dan perlambatan pada kendaraan tersebut. Jarak pandangan henti adalah jarak yang dibutuhkan oleh pengendara untuk menghentikan kendaraannya yang bergerak setelah melihat adanya rintangan pada lajur jalannya. Penelitian ini ingin mengetahui perilaku pengendara dan jarak pandang henti yang ideal bagi pengendara sepeda motor matic. Model Multi linear Regression hubungan Jarak pandangan henti dengan variable kecepatan, kapasitas mesin dan jenis rem diteliti. Hasilnya diperoleh jarak henti ideal yang dipengaruhi oleh kecepatan, kapasitas mesin, dan jenis rem depan.

Abstract 4001: Relationship between Exposure to the Prasugrel Active Metabolite with TIMI Major/Minor Bleeding in TRITON-TIMI 38

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Daniel E Salazar ◽  
C. Steven Ernest ◽  
Rebecca E Wrishko ◽  
Govinda J Weerakkody ◽  
David S Small ◽  
...  
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Active Metabolite ◽  
Study Drug ◽  
Minor Bleeding ◽  
Loading Dose ◽  
Lower Quartile ◽  
Risk Of Bleeding ◽  
Multi Linear Regression ◽  
The Relationship

In TRITON-TIMI 38, patients treated with prasugrel had a higher incidence of TIMI bleeding compared to treatment with clopidogrel. Increased bleeding was most evident in patients <60 kg or ≥75 years. The relationship between exposure to prasugrel active metabolite (Pras-AM) and TIMI Major/Minor (M/M) bleeding was assessed in 1159 patients enrolled in the TRITON pharmacokinetic substudy ~17% of treated population. The relationship between exposure and bleeding was also assessed in the subset of patients <60 kg or ≥75 years. A multi-linear regression model was used to quantitatively predict Pras-AM from measurement of its 2 downstream inactive metabolites. Exposure quartiles for Pras-AM were constructed for all patients, as well as for patients ≥60 kg or <75 years. TIMI bleeding by exposure quartiles was assessed. The risk of bleeding for patients <60 kg or ≥75 years was assessed using the quartiles constructed for the complementary population. Relationship between exposure and bleeding was analyzed through 3 days from the first dose of study drug to evaluate the effect of the loading dose (LD; prasugrel 60 mg) and after 3 days from the first dose of study drug to evaluate the effect of the maintenance dose (MD; prasugrel 10 mg). In the overall population, a higher estimated exposure to Pras-AM was associated with a higher incidence of bleeding after 3 days (P<0.05), but not through 3 days from the first dose of study drug. For patients ≥75 years, TIMI M/M bleeding was higher in the upper 2 quartiles of exposure (12.5%) compared to the lower 2 quartiles (2.5%). Patients ≥75 years in the lower quartile of exposure to Pras-AM had similar TIMI M/M bleeding compared to patients <75 years. For patients <60 kg, TIMI M/M bleeding was observed only in the upper quartile of exposure (14.8%). Increased estimated exposure to Pras-AM with the MD was associated with increased bleeding but exposure during LD was not associated with increased bleeding. In patients ≥75 years or <60 kg, increased TIMI M/M bleeding was confined to patients in the highest exposure quartiles to Pras-AM. Patients <75 years or 60 kg in the lower estimated exposure quartiles to Pras-AM had similar TIMI M/M bleeding compared to patients <75 years or ≥60 kg, respectively.

scholarly journals Multi-linear regression model for chlorine consumption by waters

2020 ◽  
Vol 26 (4) ◽  
pp. 200402-0
Author(s):  
Guocheng Zhu ◽  
Shanshan Zhang ◽  
Yongning Bian ◽  
Andrew S Hursthouse
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Drinking Water Treatment ◽  
Model Combination ◽  
Water Matrix ◽  
Matrix Properties ◽  
Multi Linear Regression ◽  
The Relationship

In drinking water treatment, disinfection is a key step to ensure the safety of water quality and people's health but little is known of the relationship between chlorine consumption and water matrix properties from varied sources (BWM). In this study, we measured the fluorescence from fractions of NOM (FFN) for the relevant BWM. This included the evaluation of three components: the chlorine-dependence factor (CDF) (DOC and NH3-N), the BWM (such as NO3<sup>-</sup>, NO2<sup>-</sup> and turbidity), and FFN (I-V fluorescence fractions). Multi-linear regression model was used to fit the data. Results showed that when using the CDF, BWM and FNN, in the prediction of chlorine consumption showed the (R<sup>2</sup>) values were 0.72, 0.71 and 0.41, respectively. While the FNN did not fit the model well it did enhance the model using CDF by 11.26%. The FNN is not effective in enhancement of the BWM response to the model. Combination of the CDF, BWM and FNN or that of the CDF and BWM were both effective in prediction of chlorine consumption.

scholarly journals A Multi Linear Regression Model to Derive Dust PM10 in the Sahel Using AERONET Aerosol Optical Depth and CALIOP Aerosol Layer Products

2020 ◽  
Vol 12 (18) ◽  
pp. 3099
Author(s):  
Jean-François Léon ◽  
Nadège Martiny ◽  
Sébastien Merlet
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Linear Regression Model ◽  
Population Exposure ◽  
Aerosol Layer ◽  
Multi Linear Regression ◽  
Sun Photometer ◽  
The Impact

Due to a limited number of monitoring stations in Western Africa, the impact of mineral dust on PM10 surface concentrations is still poorly known. We propose a new method to retrieve PM10 dust surface concentrations from sun photometer aerosol optical depth (AOD) and CALIPSO/CALIOP Level 2 aerosol layer products. The method is based on a multi linear regression model that is trained using co-located PM10, AERONET and CALIOP observations at 3 different locations in the Sahel. In addition to the sun photometer AOD, the regression model uses the CALIOP-derived base and top altitude of the lowermost dust layer, its AOD, the columnar total and columnar dust AOD. Due to the low revisit period of the CALIPSO satellite, the monthly mean annual cycles of the parameters are used as predictor variables rather than instantaneous observations. The regression model improves the correlation coefficient between monthly mean PM10 and AOD from 0.15 (AERONET AOD only) to 0.75 (AERONET AOD and CALIOP parameters). The respective high and low PM10 concentration during the winter dry season and summer season are well produced. Days with surface PM10 above 100 μg/m3 are better identified when using the CALIOP parameters in the multi linear regression model. The number of true positives (actual and predicted concentrations above the threshold) is increased and leads to an improvement in the classification sensitivity (recall) by a factor 1.8. Our methodology can be extrapolated to the whole Sahel area provided that satellite derived AOD maps are used in order to create a new dataset on population exposure to dust events in this area.

Examination of the relationship between inbreeding and population size

1985 ◽  
Vol 17 (1) ◽  
pp. 97-106 ◽  
Author(s):  
John H. Relethford
Keyword(s):  
Population Structure ◽  
Linear Regression ◽  
Population Size ◽  
Effective Population Size ◽  
Linear Regression Model ◽  
Historical Change ◽  
Human Populations ◽  
Effective Population ◽  
The Common ◽  
The Relationship

SummaryA method is presented for examining the relationship between effective population size and accumulated random inbreeding in human populations. For a set of populations, the inverse of inbreeding is regressed on effective population size using a linear regression model. This procedure allows testing of several hypotheses regarding the common and unique influences on population structure. Deviations from the expected curve suggest demographic or historical change. This method is applied to surname data from nine Irish isolates. The results show that the method is very useful in assessing differential influences on population structure.

Truck braking distance and speed estimates

1986 ◽  
Vol 13 (4) ◽  
pp. 412-422 ◽  
Author(s):  
Francis P. D. Navin
Keyword(s):  
Traffic Accident ◽  
Centre Of Mass ◽  
Average Ability ◽  
Sight Distance ◽  
Truck Accidents ◽  
Police Agencies ◽  
Braking Distance ◽  
Stopping Sight Distance ◽  
Basic Equations ◽  
Final Equation

The most frequently cited cause of truck accidents is “speed too fast for prevailing conditions.” To cite this cause, a speed estimate is necessary. This paper shows the factors that should be considered. The factors most useful in estimating a truck's braking capability include vehicle configuration, loading, location of the centre of mass, and axles with brakes. The exact value of some of the variables is difficult to obtain.The formulation proposed in this paper builds on a simple and effective procedure used by police agencies to estimate speed from skid marks. The formula given by R. Rivers' “Traffic accident investigator's handbook” is formalized and the elements in his correction factor N are derived. Basic equations for the braking of straight trucks and combinations are derived. The difficulty of implementing the equations in practice for all but the simplest situation is obvious from the complexity of the equations. A lumping of all the parameters into a simplified form is developed based on truck stopping distances obtained from published experimental data. All the trucks in the data had well-adjusted brakes. The final equation to estimate speed from a truck's skid marks accounts for the average ability of such vehicles to stop as well as the variance in stopping ability. Key words: truck braking, braking efficiency, stopping sight distance, skid marks.

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